The AI market is becoming "polytheistic," with numerous specialized models excelling at niche tasks, rather than "monotheistic," where a single super-model dominates. This fragmentation creates opportunities for differentiated startups to thrive by building effective models for specific use cases, as no single model has mastered everything.

The latest models from Anthropic (Opus 4.6) and OpenAI (Codex 5.3) represent two distinct engineering methodologies. Opus is an autonomous agent you delegate to, while Codex is an interactive collaborator you pair-program with. Choosing a model is now a workflow decision, not just a performance one.

Beyond raw capability, top AI models exhibit distinct personalities. Ethan Mollick describes Anthropic's Claude as a fussy but strong "intellectual writer," ChatGPT as having friendly "conversational" and powerful "logical" modes, and Google's Gemini as a "neurotic" but smart model that can be self-deprecating.

New models like Fable and GPT 5.6 are developing distinct 'personalities'. Fable acts as an autonomous agent for long, well-defined tasks, while GPT 5.6's 'Sol' variant excels at back-and-forth, iterative collaboration with the user, indicating a split in UX philosophy.

A multi-model strategy is key. Serval finds that OpenAI's models consistently excel at user-facing interactions and correctly calling tools. For backend code generation to create automations, however, Anthropic's models currently deliver superior performance, highlighting the need to match models to specific applications.

Initially, even OpenAI believed a single, ultimate 'model to rule them all' would emerge. This thinking has completely changed to favor a proliferation of specialized models, creating a healthier, less winner-take-all ecosystem where different models serve different needs.

The most advanced AI users are 'polyamorous' with models, using an average of 3.5 different tools. This indicates a mature usage pattern where users select the best model for a specific job rather than relying on a single, all-purpose AI, challenging the 'winner-take-all' market theory.

As models mature, their core differentiator will become their underlying personality and values, shaped by their creators' objective functions. One model might optimize for user productivity by being concise, while another optimizes for engagement by being verbose.

When used as agents, different foundation models show distinct working styles. GPT Codex 5.3 acts like a brilliant but abrasive engineer who rushes to build, while Claude Opus 4.6 is a more thoughtful, intuitive manager. This requires different management approaches from the human operator.